AZX aims to accelerate positive impact in critical industries through AI transformation, specializing in physics-informed ML and enterprise AI solutions to address climate and sustainability challenges.
Requirements
- 5+ years building and deploying ML systems in production environments
- Expert-level Python and experience with PyTorch / TensorFlow
- Deep expertise in at least one domain: NLP, Computer Vision, Time-Series, or Reinforcement Learning
- Generative AI and LLM-related capabilities (e.g., prompt engineering, RAG, fine-tuning, LangChain, model evaluation tooling)
- MLOps and infrastructure automation (e.g., CI/CD for ML, Docker, Kubernetes, Terraform, MLflow, Kubeflow)
- Strong engineering fundamentals: system design, scalability, testing, and monitoring
- Track record of translating ambiguous business problems into production ML solutions
Responsibilities
- Turn ambiguous client problems into shipping code.
- Drive projects from discovery to deployment
- Design and write clean, scalable code at appropriate quality standards (sometimes “right”, and sometimes “right now”).
- Design, integrate, and productionize ML solutions including predictive models, GenAI systems, physics-informed ML, and digital twins.
- Collaborate with domain experts in energy, real estate, and climate to translate business needs into ML solutions
- Advocate for engineering best practices and positive dev culture
Other
- High emotional intelligence and a learning mindset
- Strong collaboration skills
- Enjoy others' success and a fun, positive environment.
- Comfortable making decisions in the face of ambiguity and course correcting as needed.
- Experience in both startup and enterprise environments
